Autonomous soaring has the potential to greatly improve both the range and endurance of small robotic aircraft. This paper describes an autonomous soaring system that generates a dynamic map of lift sources (thermals) in the environment and uses this map for online flight planning and decision making. Components of the autonomy algorithm include thermal mapping, explore/exploit decision making, navigation, optimal airspeed computation, thermal centering control, and energy state estimation. A finite state machine manages the aircraft behavior during flight and determines when changing behavior is appropriate. A complete system to enable autonomous soaring is described with special attention paid to practical considerations encountered during flight testing. A companion paper describes the hardware implementation of this system and the results of a flight test campaign conducted at Aberdeen Proving Ground in September 2015.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications